An inertial navigation system (INS) is one that uses inertial sensors attached to a moving platform to provide a navigation solution in terms of its position, velocity, and attitude (PVA) as it moves. Traditionally, the navigation device is firmly tethered to the moving platform so that the sensor axes are constrained to coincide with the forward, transversal, and vertical axes of the platform. In the event of improper sensor alignment (or misalignment), the inertial sensors will not measure the true motion of the platform but rather a component that is offset proportional to the degree to which the sensor and platform axes are misaligned. This, in turn, causes the positions and attitude calculated using the measurements from the inertial sensors to not be representative of the true state of the platform.
A portable navigation device, however, is inherently untethered and not constrained to any particular orientation with respect to the platform.
Existing portable navigation devices cannot achieve accurate position and attitude of the platform unless the absolute attitude angles for the device and the platform are known. Alternatively one can use the absolute attitude angle for the device and misalignment between the device and platform, or vice versa. The former approach requires a sensor assembly on both the device and platform and can be impractical for a portable navigation device. As such, knowledge of misalignment is a key factor in enabling an accurate navigation solution.
An exponential increase in functionality and reduction of size has led to widespread adoption of mobile navigation-capable devices such as smartphones and tablets. One notable feature is that these devices are increasingly being equipped with high-sensitivity Assisted Global Positioning System (AGPS) chipsets, which in addition to significantly improving the startup performance by utilizing network connection, also further use high sensitivity capabilities to provide an absolute position of the platform even in environments without a clear line of sight to the GPS satellites. In environments where AGPS information alone is not enough, such as downtown or deep indoors, one possible solution is to incorporate the use of one or more cell towers for a much coarser solution. These positioning methods are available in many mobile devices, however accurate indoor localization still presents a challenge and fails to satisfy the accuracy demands of current location based services (LBS). Additionally, these methods may only provide the absolute heading of the platform without any information on the device's heading.
Another notable feature of mobile navigation-capable devices is that many come equipped with Micro Electro Mechanical System (MEMS) sensors such as accelerometers and gyroscopes. These sensors have not been extensively used for navigation purposes due to their very high noise, large random drift rates, and the frequently changing orientations of the device with respect to the platform. They have hitherto been relegated to limited uses such as for screen control and entertainment applications. More feature-rich devices come equipped with magnetometers and it has been shown that a navigation solution using accelerometers and magnetometers may be possible if the user is careful enough to keep the device in a specific, unchanging orientation with respect to their body; however, this is not a common use case.
It is evident that there is a need for a method of accurately utilizing measurements from a navigation-capable device within a platform to determine the navigation state of the device/platform without any constraints on either the platform (i.e. in indoor or outdoor environments) or the mobility of the device within the platform (i.e. with no restriction on the device orientation). The needed method should allow the device to be tilted in any orientation while still providing seamless navigation information without a degradation in performance.
In addition to the above mentioned application of portable devices (that include a full navigation solution including position, velocity and attitude, or position and attitude), there are other applications (that may include estimating a full navigation solution, or an attitude only solution or an attitude and velocity solution) where the needed method is aimed at enhancing the user experience and usability, and may be applicable in a number of scenarios such as gaming or augmented reality applications.
Some currently existing misalignment estimation techniques calculate only discrete or pre-determined values of the misalignment angle, or a continuous misalignment angle over the full range of possibilities based on values obtained from inertial sensor measurements. There are scenarios in which inertial sensor-based methods fail to resolve the misalignment angle to the desired accuracy. Examples of such scenarios include those in which the device is undergoing very slow motion or the user of such devices walks with a problematic gait. Furthermore, as many of these sensors (especially those found in portable devices) suffer from the effects of various errors that change with time, they can be problematic for stable, long term device angle determination.
As such, there is a need for a method and apparatus to calculate the angle between the device and the platform that is able to work for any device usage or orientation with respect to the platform and that does not rely on the noisy inertial sensor measurements.